Incident Analysis and Prediction of Safety Performance on Construction Sites
The hazardous nature of the construction environment and current incident statistics indicate a pressing need for safety performance improvement. One potential approach is the strategic analysis of leading indicators for measuring safety performance as opposed to using only lagging indicators, which...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-07-01
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| Series: | CivilEng |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4109/3/3/39 |
| _version_ | 1827662298443939840 |
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| author | Ibukun Awolusi Eric Marks Alexander Hainen Ammar Alzarrad |
| author_facet | Ibukun Awolusi Eric Marks Alexander Hainen Ammar Alzarrad |
| author_sort | Ibukun Awolusi |
| collection | DOAJ |
| description | The hazardous nature of the construction environment and current incident statistics indicate a pressing need for safety performance improvement. One potential approach is the strategic analysis of leading indicators for measuring safety performance as opposed to using only lagging indicators, which has protractedly been the norm. This study presents a systematic safety performance measurement framework and statistical modeling processes for analyzing safety incident data for accident prediction and prevention on construction sites. Using safety incident data obtained from a construction corporation that implements proactive safety management programs, statistical modeling processes are utilized to identify variables with high correlations of events and incidents that pose dangers to the safety and health of workers on construction sites. The findings of the study generated insights into the different types and impacts of incident causal factors and precursors on injuries and accidents on construction sites. One of the key contributions of this study is the promotion of proactive methods for improving safety performance on construction sites. The framework and statistical models developed in this study can be used to collect and analyze safety data to provide trends in safety performance, set improvement targets, and provide continuous feedback to enhance safety performance on construction sites. |
| first_indexed | 2024-03-10T00:23:07Z |
| format | Article |
| id | doaj.art-c4a1b210c4fc4dd7bbdb6c08d41020ee |
| institution | Directory Open Access Journal |
| issn | 2673-4109 |
| language | English |
| last_indexed | 2024-03-10T00:23:07Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | CivilEng |
| spelling | doaj.art-c4a1b210c4fc4dd7bbdb6c08d41020ee2023-11-23T15:39:41ZengMDPI AGCivilEng2673-41092022-07-013366968610.3390/civileng3030039Incident Analysis and Prediction of Safety Performance on Construction SitesIbukun Awolusi0Eric Marks1Alexander Hainen2Ammar Alzarrad3School of Civil & Environmental Engineering, and Construction Management, The University of Texas at San Antonio, San Antonio, TX 78207, USASchool of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30313, USADepartment of Civil, Construction and Environmental Engineering, University of Alabama, Tuscaloosa, AL 35487, USADepartment of Civil Engineering, Marshall University, Huntington, WV 25755, USAThe hazardous nature of the construction environment and current incident statistics indicate a pressing need for safety performance improvement. One potential approach is the strategic analysis of leading indicators for measuring safety performance as opposed to using only lagging indicators, which has protractedly been the norm. This study presents a systematic safety performance measurement framework and statistical modeling processes for analyzing safety incident data for accident prediction and prevention on construction sites. Using safety incident data obtained from a construction corporation that implements proactive safety management programs, statistical modeling processes are utilized to identify variables with high correlations of events and incidents that pose dangers to the safety and health of workers on construction sites. The findings of the study generated insights into the different types and impacts of incident causal factors and precursors on injuries and accidents on construction sites. One of the key contributions of this study is the promotion of proactive methods for improving safety performance on construction sites. The framework and statistical models developed in this study can be used to collect and analyze safety data to provide trends in safety performance, set improvement targets, and provide continuous feedback to enhance safety performance on construction sites.https://www.mdpi.com/2673-4109/3/3/39analysisconstruction safety performanceleading and lagging indicatorspredictionsafety incident datastatistical models |
| spellingShingle | Ibukun Awolusi Eric Marks Alexander Hainen Ammar Alzarrad Incident Analysis and Prediction of Safety Performance on Construction Sites CivilEng analysis construction safety performance leading and lagging indicators prediction safety incident data statistical models |
| title | Incident Analysis and Prediction of Safety Performance on Construction Sites |
| title_full | Incident Analysis and Prediction of Safety Performance on Construction Sites |
| title_fullStr | Incident Analysis and Prediction of Safety Performance on Construction Sites |
| title_full_unstemmed | Incident Analysis and Prediction of Safety Performance on Construction Sites |
| title_short | Incident Analysis and Prediction of Safety Performance on Construction Sites |
| title_sort | incident analysis and prediction of safety performance on construction sites |
| topic | analysis construction safety performance leading and lagging indicators prediction safety incident data statistical models |
| url | https://www.mdpi.com/2673-4109/3/3/39 |
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